"Lua" matching MCP servers:

Enables agents to store and recall long-term memories by semantic relevance rather than exact keywords, with writes gated by verbatim evidence and separate memory stores per agent mode.

Provides AI agents with institutional-grade quantitative finance tools including real-time market data, paper trading via Alpaca, risk analysis with Monte Carlo simulations, backtesting, and multi-source news sentiment analysis for portfolio management and trading strategy development.

Enables academic literature management through PDF import, hybrid search, knowledge graph construction, and automated literature review generation. Combines full-text search with semantic vector search for comprehensive paper analysis.

Enables AI agents to search a Mac's documents by content using a local index, returning ranked paths and matching snippets. It supports formats like PDF, DOCX, HWP, and OCR'd scans, with Korean-aware search, while keeping everything offline and without requiring filesystem access.